Detailed maps and more accurate weather forecasts of urban Helsinki with aeroplane-mounted laser
Urban surface cover largely determines surface–atmosphere interactions. The replacement of pervious surfaces and vegetation by impervious materials alters the surface energy budget. Most notably, the available energy is used for the vertical turbulent sensible heat flux rather than evaporation, leading to the intensification of the inadvertent urban-heat-island effect, observed in many cities. The reduced evaporation and percolation are accompanied by a larger water runoff, and together they affect the water balance of a city and cause a higher flood risk. The lack of vegetation also minimizes carbon dioxide (CO2) uptake via photosynthesis and reduces the buffering effect of air pollutants.
Finnish Meteorological Institute's researchers have published one of the largest studies of an urban to suburban area (6x9 km) classified based on lidar scanning data from flights. The aim of the study was to create a detailed map of the terrain of Helsinki, and to see how large is the effect of the terrain resolution on urban-weather-forecasting accuracy.
Lidar is a remote-sensing technology – a prime use is measuring distance by illuminating a target with a laser and analyzing the reflected light. Airborne laser/lidar scanning was performed on many flights in 2008, producing millions of datapoints from Helsinki alone. The data are part of an open database that aims to provide for Finland a nationwide lidar-scanning coverage for the determination of a new digital elevation model with 2-metre resolution. In addition to the lidar data, FMI's researchers used geographical information on the coastline and building edges from The Helsinki Region Environmental Services' (HSY) database. The land cover of an urban/suburban area (6x9km) of southern Helsinki was classified into six classes: buildings, grass, shrubs, trees, water and roads/bridges/rock/sand.
Weather forecasting for cities is reliant upon a key weather-forecast component known as the urban surface-energy budget. One such budget, SUEWS, was tested by varying land-surface-cover types to estimate the impact upon weather conditions in the city (i.e. the so-called turbulent heat flux and evaporative fluxes). SUEWS simulates the energy and water budgets at a local/neighbourhood scale using meteorological input data and information about the land surface cover. SUEWS model results were compared with flux measurements in downtown Helsinki on Hotel Torni.
The terrain maps were produced, and had a 95% accuracy. Surface cover types and their share on the whole study area were water (33%), impervious (27%), high vegetation (16%), buildings (13%), grass (9%), and low vegetation (2%). On the smaller study area in downtown Helsinki (a circle 1km radius from Hotel Torni) types and their shares were 41% impervious, 37% buildings, 12% high vegetation, 7% grass, 3% low vegetation. The average building height was 24 m.
Street trees are only visible in the 2-metre resolution dataset – they disappear already at resolutions of 10 metres and coarser. An artificial aggregation of the surface-cover map in the model input data, from 2 to 100 m, reduced the fraction of vegetation by twothirds: resulting in a 16% increase in simulated heat flux and a 56% reduction in evaporative flux. All statistics showed systematic worsening of the model performance with coarsening horizontal surface resolution. For improved accuracy of weather-prediction models for cities, we thus recommend having surface-cover data with 2-metre resolution over cities with street trees, or other patchy vegetation.
Further information
Senior Researcher Curtis Wood, Finnish Meteorological Institute, firstname.lastname@fmi.fi, tel. +358504058034
Nordbo A, Karsisto P, Matikainen L, Wood CR, Järvi L. Urban surface cover determined with airborne lidar at 2 m resolution – Implications for surface energy balance modelling. Urban Climate (2015).